mlomnitz / DiffJPEG

DiffJPEG: A PyTorch implementation

This is a pytorch implementation of differentiable jpeg compression algorithm. This work is based on the discussion in this paper. The work relies heavily on the tensorflow implementation in this repository

Requirements

• Pytorch 1.0.0
• numpy 1.15.4

Use

DiffJPEG functions as a standard pytorch module/layer. To use, first import the layer and then initialize with the desired parameters:

• differentaible(bool): If true uses custom differentiable rounding function, if false uses standrard torch.round
• quality(float): Quality factor for jpeg compression scheme.

from DiffJPEG import DiffJPEG
jpeg = DiffJPEG(hieght=224, width=224, differentiable=True, quality=80)